443 results on '"Zuo, Renguang"'
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2. A Heterogeneous Graph Construction Method for Mineral Prospectivity Mapping
3. Incorporating Geological Knowledge into Deep Learning to Enhance Geochemical Anomaly Identification Related to Mineralization and Interpretability
4. Causal Discovery and Deep Learning Algorithms for Detecting Geochemical Patterns Associated with Gold-Polymetallic Mineralization: A Case Study of the Edongnan Region
5. Monitoring Mining Activity and Vegetation Recovery in Rare Earth Element Mining Areas
6. Geologically Constrained Convolutional Neural Network for Mineral Prospectivity Mapping
7. Effects of Fluid Pressure Development on Hydrothermal Mineralization via Cellular Automaton Simulation
8. Dual-Branch Convolutional Neural Network and Its Post Hoc Interpretability for Mapping Mineral Prospectivity
9. An Interpretable Graph Attention Network for Mineral Prospectivity Mapping
10. ArcMPM: An ArcEngine-Based Software for Mineral Prospectivity Mapping via Artificial Intelligence Algorithms
11. A Monte Carlo-based Workflow for Geochemical Anomaly Identification Under Uncertainty and Global Sensitivity Analysis of Model Parameters
12. Machine Learning-Based Mapping for Mineral Exploration
13. A New Generation of Artificial Intelligence Algorithms for Mineral Prospectivity Mapping
14. Geological Mapping Using Direct Sampling and a Convolutional Neural Network Based on Geochemical Survey Data
15. Deep Reinforcement Learning for Mineral Prospectivity Mapping
16. Geologically constrained unsupervised dual-branch deep learning algorithm for geochemical anomalies identification
17. Multivariate statistical analysis and bespoke deviation network modeling for geochemical anomaly detection of rare earth elements
18. Fusion of GaoFen-5 and Sentinel-2B data for lithological mapping using vision transformer dynamic graph convolutional network
19. Geochemical survey data cube: A useful tool for lithological classification and geochemical anomaly identification
20. Multifractals
21. Metallogenic-Factor Variational Autoencoder for Geochemical Anomaly Detection by Ad-Hoc and Post-Hoc Interpretability Algorithms
22. Revealing Geochemical Patterns Associated with Mineralization Using t-Distributed Stochastic Neighbor Embedding and Random Forest
23. A physically constrained hybrid deep learning model to mine a geochemical data cube in support of mineral exploration
24. Leucogranite mapping via convolutional recurrent neural networks and geochemical survey data in the Himalayan orogen
25. Quantification of Uncertainty Associated with Evidence Layers in Mineral Prospectivity Mapping Using Direct Sampling and Convolutional Neural Network
26. Mineral Prospectivity Mapping Using Deep Self-Attention Model
27. Graph Deep Learning Model for Mapping Mineral Prospectivity
28. An interpretable attention branch convolutional neural network for identifying geochemical anomalies related to mineralization
29. The graph attention network and its post-hoc explanation for recognizing mineralization-related geochemical anomalies
30. Machine learning for analysis of geo-exploration data
31. List of contributors
32. The geographical information system toolbox for mineral exploration
33. Lithological Mapping Using a Convolutional Neural Network based on Stream Sediment Geochemical Survey Data
34. Visual Interpretable Deep Learning Algorithm for Geochemical Anomaly Recognition
35. Modeling singular mineralization processes due to fluid pressure fluctuations
36. Mineral Prospectivity Mapping via Gated Recurrent Unit Model
37. A Geologically Constrained Variational Autoencoder for Mineral Prospectivity Mapping
38. A Physically Constrained Variational Autoencoder for Geochemical Pattern Recognition
39. Robust Feature Extraction for Geochemical Anomaly Recognition Using a Stacked Convolutional Denoising Autoencoder
40. A fractal model of granitic intrusion and variability based on cellular automata
41. Late Mesozoic to Cenozoic exhumation of the SE South China Block: Constraints from zircon and apatite fission-track thermochronology
42. Model averaging for identification of geochemical anomalies linked to mineralization
43. A geologically-constrained deep learning algorithm for recognizing geochemical anomalies
44. GIS, Geostatistics, and Machine Learning in Medical Geology
45. Mapping prospectivity for regolith-hosted REE deposits via convolutional neural network with generative adversarial network augmented data
46. Mineral prospectivity mapping using a joint singularity-based weighting method and long short-term memory network
47. Uncertainties in GIS-Based Mineral Prospectivity Mapping: Key Types, Potential Impacts and Possible Solutions
48. Knowledge discovery of geochemical patterns from a data-driven perspective
49. Distinguishing IOCG and IOA deposits via random forest algorithm based on magnetite composition
50. Mapping geochemical anomalies by accounting for the uncertainty of mineralization-related elemental associations
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